Search results for: identification partial rbcL

Authors: O. O. Fola-Matthews, O. O. Soyinka, D. N. Bitalo

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Nigeria is one of the major shark fishing nations in Africa, but its fisheries managers still record catch data in aggregates ‘sharks’ with no species-specific details. This is because most of the shark specimens look identical in morphology, and field identification of some closely related species is tricky. This study uses DNA barcoding as a method to identify shark species from five different landing areas off the Nigerian Coast. 100 dorsal fins were sampled in order to provide a Chondrichthyan sequence that would be matched to reference specimens in a DNA barcode database

Keywords: BOLD, DNA barcoding, nigeria, sharks

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Authors: Mallikarjun Warad, C. M. Kalleshwaraswamy, P. R. Shashank

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Studies were conducted to record the occurrence of different species of hairy caterpillar on different host plants in and around Shivamogga, Karnataka, India. Twelve genera of hairy caterpillars belonging to Arctiinae and Lymantriinae were recorded on different host plants and reared to adults in laboratory on their respective hosts. The Porthesia sp. feed on castor, Creatonotus gangis on cocoa, Perina nuda on fig, Pericalia ricini on pigeon pea, Utetheisa pulchella on sunhemp and Euproctis sp. on paddy and banana. Illustrations of immature and adults were made to associate them. Along with this, light traps were also set during the rainy season, to capture adults of hairy caterpillars. An illustrated identification key was provided for easy and accurate identification of adult of hairy caterpillars based on their morphological (male genitalial) characters. The study through a light on the existence of sexual dimorphism, polyphagous nature and diapause are the major hindrance in taxonomic identification. Hence, attempts were made to address these issues in the study.

Keywords: Erebidae, hairy caterpillars, male genitalia, taxonomy

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Camilla Elphick, Graham Hole, Samuel Hutton, Graham Pike

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Pupil size has been found to change irrespective of luminosity, suggesting that it can be used to make inferences about cognitive processes, such as cognitive load. To see whether identifying a target requires a different cognitive load to rejecting distractors, the effect of viewing a target (compared with viewing distractors) on pupil size was investigated using a sequential video lineup procedure with two lineup sessions. Forty one participants were chosen randomly via the university. Pupil sizes were recorded when viewing pre target distractors and post target distractors and compared to pupil size when viewing the target. Overall, pupil size was significantly larger when viewing the target compared with viewing distractors. In the first session, pupil size changes were significantly different between participants who identified the target (Hits) and those who did not. Specifically, the pupil size of Hits reduced significantly after viewing the target (by 26%), suggesting that cognitive load reduced following identification. The pupil sizes of Misses (who made no identification) and False Alarms (who misidentified a distractor) did not reduce, suggesting that the cognitive load remained high in participants who failed to make the correct identification. In the second session, pupil sizes were smaller overall, suggesting that cognitive load was smaller in this session, and there was no significant difference between Hits, Misses and False Alarms. Furthermore, while the frequency of Hits increased, so did False Alarms. These two findings suggest that the benefits of including a second session remain uncertain, as the second session neither provided greater accuracy nor a reliable way to measure it. It is concluded that pupil size is a measure of face recognition strength in the first session of a target present lineup procedure. However, it is still not known whether cognitive load is an adequate explanation for this, or whether cognitive engagement might describe the effect more appropriately. If cognitive load and cognitive engagement can be teased apart with further investigation, this would have positive implications for understanding eyewitness identification. Nevertheless, this research has the potential to provide a tool for improving the reliability of lineup procedures.

Keywords: cognitive load, eyewitness identification, face recognition, pupillometry

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Authors: Muhammad Javed Bhatti, Tariq Ali, Muazz Ali

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Due to growing environmental awareness in Pakistan, the researchers are increasingly turning to assess and analyze properties of industrial waste and finding solutions on using industrial waste as secondary material. Due to industrialization, enormous by-products are produced and to utilize these by-products is the main challenge faced in Pakistan. Induction furnace slag is one of the industrial by-products from the iron and steel making industries. This paper highlights the true utilization of induction furnace slag as partial replacement of fine aggregate. For the experimental investigation, mixes were prepared with fine aggregate replacement using 0 percent, 5 percent, 10 percent, 15 percent, 20 percent, 25 percent, 30 percent, 35 percent and 40 percent induction furnace slag to evaluate the workability, compaction factor, compressive strength, flexural strength, modulus of elasticity.

Keywords: compressive strength, deflection, induction furnace slag, workability

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Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

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We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

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Authors: Alexander A. Stakheev, Larisa V. Samokhvalova, Sergey K. Zavriev

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Fusarium fungi are among the most devastating plant pathogens distributed all over the world. Significant reduction of grain yield and quality caused by Fusarium leads to multi-billion dollar annual losses to the world agricultural production. These organisms can also cause infections in immunocompromised persons and produce the wide range of mycotoxins, such as trichothecenes, fumonisins, and zearalenone, which are hazardous to human and animal health. Identification of Fusarium fungi based on the morphology of spores and spore-forming structures, colony color and appearance on specific culture media is often very complicated due to the high similarity of these features for closely related species. Modern Fusarium taxonomy increasingly uses data of crossing experiments (biological species concept) and genetic polymorphism analysis (phylogenetic species concept). A number of novel Fusarium sibling species has been established using DNA barcoding techniques. Species recognition is best made with the combined phylogeny of intron-rich protein coding genes and ribosomal DNA sequences. However, the internal transcribed spacer of (ITS), which is considered to be universal DNA barcode for Fungi, is not suitable for genus Fusarium, because of its insufficient variability between closely related species and the presence of non-orthologous copies in the genome. Nowadays, the translation elongation factor 1 alpha (TEF1α) gene is the “gold standard” of Fusarium taxonomy, but the search for novel informative markers is still needed. In this study, we used two novel DNA markers, frataxin (FXN) and heat shock protein 90 (HSP90) to discover phylogenetic relationships between Fusarium species. Multilocus phylogenetic analysis based on partial sequences of TEF1α, FXN, HSP90, as well as intergenic spacer of ribosomal DNA (IGS), beta-tubulin (β-TUB) and phosphate permease (PHO) genes has been conducted for 120 isolates of 19 Fusarium species from different climatic zones of Russia and neighboring countries using maximum likelihood (ML) and maximum parsimony (MP) algorithms. Our analyses revealed that FXN and HSP90 genes could be considered as informative phylogenetic markers, suitable for evolutionary and taxonomic studies of Fusarium genus. It has been shown that PHO gene possesses more variable (22 %) and parsimony informative (19 %) characters than other markers, including TEF1α (12 % and 9 %, correspondingly) when used for elucidating phylogenetic relationships between F. avenaceum and its closest relatives – F. tricinctum, F. acuminatum, F. torulosum. Application of novel DNA barcodes confirmed the fact that F. arthrosporioides do not represent a separate species but only a subspecies of F. avenaceum. Phylogeny based on partial PHO and FXN sequences revealed the presence of separate cluster of four F. avenaceum strains which were closer to F. torulosum than to major F. avenaceum clade. The strain F-846 from Moldova, morphologically identified as F. poae, formed a separate lineage in all the constructed dendrograms, and could potentially be considered as a separate species, but more information is needed to confirm this conclusion. Variable sites in PHO sequences were used for the first-time development of specific qPCR-based diagnostic assays for F. acuminatum and F. torulosum. This work was supported by Russian Foundation for Basic Research (grant № 15-29-02527).

Keywords: DNA barcode, fusarium, identification, phylogenetics, taxonomy

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Authors: Isaac Quiros-Fernandez, Angel Cid-Arregui

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Tumor-reactive T cell receptors (TCRs) are being subject of intense investigation since they offer great potential in adoptive cell therapies against cancer. However, the identification of tumor-specific TCRs has proven challenging, for instance, due to the limited expansion capacity of tumor-infiltrating T cells (TILs) and the extremely low frequencies of tumor-reactive T cells in the repertoire of patients and healthy donors. We have developed an approach for rapid identification and characterization of neoepitope-reactive TCRs from the T cell repertoire of healthy donors. CD8 T cells isolated from multiple donors are subjected to a first sorting step after staining with HLA multimers carrying the peptide of interest. The isolated cells are expanded for two weeks, after which a second sorting is performed using the same peptide-HLA multimers. The cells isolated in this way are then processed for single-cell sequencing of their TCR alpha and beta chains. Newly identified TCRs are cloned in appropriate expression vectors for functional analysis on Jurkat, NK92, and primary CD8 T cells and tumor cells expressing the appropriate antigen. We have identified TCRs specifically binding HLA-A2 presenting epitopes of tumor antigens, which are capable of inducing TCR-mediated cell activation and cytotoxicity in target cancer cell lines. This method allows the identification of tumor-reactive TCRs in about two to three weeks, starting from peripheral blood samples of readily available healthy donors.

Keywords: cancer, TCR, tumor antigens, immunotherapy

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Authors: C. Virgilio, J. Carlier, P. Campistron, M. Toubal, P. Garnier, L. Broussous, V. Thomy, B. Nongaillard

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Wetting efficiency of microstructures or nanostructures patterned on Si wafers is a real challenge in integrated circuits manufacturing. In fact, bad or non-uniform wetting during wet processes limits chemical reactions and can lead to non-complete etching or cleaning inside the patterns and device defectivity. This issue is more and more important with the transistors size shrinkage and concerns mainly high aspect ratio structures. Deep Trench Isolation (DTI) structures enabling pixels’ isolation in imaging devices are subject to this phenomenon. While low-frequency acoustic reflectometry principle is a well-known method for Non Destructive Test applications, we have recently shown that it is also well suited for nanostructures wetting characterization in a higher frequency range. In this paper, we present a high-frequency acoustic reflectometry characterization of DTI wetting through a confrontation of both experimental and modeling results. The acoustic method proposed is based on the evaluation of the reflection of a longitudinal acoustic wave generated by a 100 µm diameter ZnO piezoelectric transducer sputtered on the silicon wafer backside using MEMS technologies. The transducers have been fabricated to work at 5 GHz corresponding to a wavelength of 1.7 µm in silicon. The DTI studied structures, manufactured on the wafer frontside, are crossing trenches of 200 nm wide and 4 µm deep (aspect ratio of 20) etched into a Si wafer frontside. In that case, the acoustic signal reflection occurs at the bottom and at the top of the DTI enabling its characterization by monitoring the electrical reflection coefficient of the transducer. A Finite Difference Time Domain (FDTD) model has been developed to predict the behavior of the emitted wave. The model shows that the separation of the reflected echoes (top and bottom of the DTI) from different acoustic modes is possible at 5 Ghz. A good correspondence between experimental and theoretical signals is observed. The model enables the identification of the different acoustic modes. The evaluation of DTI wetting is then performed by focusing on the first reflected echo obtained through the reflection at Si bottom interface, where wetting efficiency is crucial. The reflection coefficient is measured with different water / ethanol mixtures (tunable surface tension) deposited on the wafer frontside. Two cases are studied: with and without PFTS hydrophobic treatment. In the untreated surface case, acoustic reflection coefficient values with water show that liquid imbibition is partial. In the treated surface case, the acoustic reflection is total with water (no liquid in DTI). The impalement of the liquid occurs for a specific surface tension but it is still partial for pure ethanol. DTI bottom shape and local pattern collapse of the trenches can explain these incomplete wetting phenomena. This high-frequency acoustic method sensitivity coupled with a FDTD propagative model thus enables the local determination of the wetting state of a liquid on real structures. Partial wetting states for non-hydrophobic surfaces or low surface tension liquids are then detectable with this method.

Keywords: wetting, acoustic reflectometry, gigahertz, semiconductor

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Anupuma Raina, Ajay Parkash

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In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

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Authors: Davood Yazdani Cherati, Hussein Hashemi Senejani

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In this paper, a convenient analytical solution for a system of coupled differential equations, derived from thermo-hydro-mechanical analysis of three-phase porous media such as unsaturated soils is developed. This kind of analysis can be used in various fields such as geothermal energy systems and seepage of leachate from buried municipal and domestic waste in geomaterials. Initially, a system of coupled differential equations, including energy, mass, and momentum conservation equations is considered, and an analytical method called AGM is employed to solve the problem. The method is straightforward and comprehensible and can be used to solve various nonlinear partial differential equations (PDEs). Results indicate the accuracy of the applied method for solving nonlinear partial differential equations.

Keywords: AGM, analytical solution, porous media, thermo-hydro-mechanical, unsaturated soils

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Authors: Lotfi O. Gargab, Ruichong R. Zhang

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A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

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Authors: Davide Gotti, Milan Prodanovic, Sergio Pinilla, David Muñoz-Torrero

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Since its proposal, the Doyle-Fuller-Newman (DFN) lithium-ion battery model has gained popularity in the electrochemical field. In fact, this model provides the user with theoretical support for designing the lithium-ion battery parameters, such as the material particle or the diffusion coefficient adjustment direction. However, the model is mathematically complex as it is composed of several partial differential equations (PDEs) such as Fick’s law of diffusion, the MacInnes and Ohm’s equations, among other phenomena. Thus, to efficiently use the model in a time-domain simulation environment, the selection of the discretization technique is of a pivotal importance. There are several numerical methods available in the literature that can be used to carry out this task. In this study, a comparison between the explicit Euler, Crank-Nicolson, and Chebyshev discretization methods is proposed. These three methods are compared in terms of accuracy, stability, and computational times. Firstly, the explicit Euler discretization technique is analyzed. This method is straightforward to implement and is computationally fast. In this work, the accuracy of the method and its stability properties are shown for the electrolyte diffusion partial differential equation. Subsequently, the Crank-Nicolson method is considered. It represents a combination of the implicit and explicit Euler methods that has the advantage of being of the second order in time and is intrinsically stable, thus overcoming the disadvantages of the simpler Euler explicit method. As shown in the full paper, the Crank-Nicolson method provides accurate results when applied to the DFN model. Its stability does not depend on the integration time step, thus it is feasible for both short- and long-term tests. This last remark is particularly important as this discretization technique would allow the user to implement parameter estimation and optimization techniques such as system or genetic parameter identification methods using this model. Finally, the Chebyshev discretization technique is implemented in the DFN model. This discretization method features swift convergence properties and, as other spectral methods used to solve differential equations, achieves the same accuracy with a smaller number of discretization nodes. However, as shown in the literature, these methods are not suitable for handling sharp gradients, which are common during the first instants of the charge and discharge phases of the battery. The numerical results obtained and presented in this study aim to provide the guidelines on how to select the adequate discretization technique for the DFN model according to the type of application to be performed, highlighting the pros and cons of the three methods. Specifically, the non-eligibility of the simple Euler method for longterm tests will be presented. Afterwards, the Crank-Nicolson and the Chebyshev discretization methods will be compared in terms of accuracy and computational times under a wide range of battery operating scenarios. These include both long-term simulations for aging tests, and short- and mid-term battery charge/discharge cycles, typically relevant in battery applications like grid primary frequency and inertia control and electrical vehicle breaking and acceleration.

Keywords: Doyle-Fuller-Newman battery model, partial differential equations, discretization, numerical methods

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Authors: Sharon Li, Zhonghang Xia

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Post-database search is an essential phase in peptide identification using tandem mass spectrometry (MS/MS) to refine peptide-spectrum matches (PSMs) produced by database search engines. These engines frequently face difficulty differentiating between correct and incorrect peptide assignments. Despite advances in statistical and machine learning methods aimed at improving the accuracy of peptide identification, challenges remain in selecting critical features for these models. In this study, two machine learning models—a random forest tree and a support vector machine—were applied to three datasets to enhance PSMs. SHAP values were utilized to determine the significance of each feature within the models. The experimental results indicate that the random forest model consistently outperformed the SVM across all datasets. Further analysis of SHAP values revealed that the importance of features varies depending on the dataset, indicating that a feature's role in model predictions can differ significantly. This variability in feature selection can lead to substantial differences in model performance, with false discovery rate (FDR) differences exceeding 50% between different feature combinations. Through SHAP value analysis, the most effective feature combinations were identified, significantly enhancing model performance.

Keywords: peptide identification, SHAP value, feature selection, random forest tree, support vector machine

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Authors: Martin Cermak, Tomas Karasek, Jaroslav Rojicek

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The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.

Keywords: genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Ali Al-Ghalib, Fouad Mohammad

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The identification of damage in reinforced concrete structures subjected to incremental cracking performance exploiting vibration data is recognized as a challenging topic in the published and heavily cited literature. Therefore, this paper attempts to shine light on the extent of dynamic methods when applied to reinforced concrete beams simulated with various scenarios of defects. For this purpose, three different reinforced concrete beams are tested through the course of the study. The three beams are loaded statically to failure in incremental successive load cycles and later rehabilitated. After each static load stage, the beams are tested under free-free support condition using experimental modal analysis. The beams were all of the same length and cross-sectional area (2.0x0.14x0.09)m, but they were different in concrete compressive strength and the type of damage presented. The experimental modal parameters as damage identification parameters were showed computationally expensive, time consuming and require substantial inputs and considerable expertise. Nonetheless, they were proved plausible for the condition monitoring of the current case study as well as structural changes in the course of progressive loads. It was accentuated that a satisfactory localization and quantification for structural changes (Level 2 and Level 3 of damage identification problem) can only be achieved reasonably through considering frequencies and mode shapes of a system in a proper analytical model. A convenient post analysis process for various datasets of vibration measurements for the three beams is conducted in order to extract, check and correlate the basic modal parameters; namely, natural frequency, modal damping and mode shapes. The results of the extracted modal parameters and their combination are utilized and discussed in this research as quantification parameters.

Keywords: experimental modal analysis, damage identification, structural health monitoring, reinforced concrete beam

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Authors: Sara Camino, Fernando Vega, Mercedes Cano, Benito Navarrete, José A. Camino

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Carbon capture and storage (CCS) technologies should play a relevant role towards low-carbon systems in the European Union by 2030. Partial oxy-combustion emerges as a promising CCS approach to mitigate anthropogenic CO₂ emissions. Its advantages respect to other CCS technologies rely on the production of a higher CO₂ concentrated flue gas than these provided by conventional air-firing processes. The presence of more CO₂ in the flue gas increases the driving force in the separation process and hence it might lead to further reductions of the energy requirements of the overall CO₂ capture process. A higher CO₂ concentrated flue gas should enhance the CO₂ capture by chemical absorption in solvent kinetic and CO₂ cyclic capacity. They have impact on the performance of the overall CO₂ absorption process by reducing the solvent flow-rate required for a specific CO₂ removal efficiency. Lower solvent flow-rates decreases the reboiler duty during the regeneration stage and also reduces the equipment size and pumping costs. Moreover, R&D activities in this field are focused on novel solvents and blends that provide lower CO₂ absorption enthalpies and therefore lower energy penalties associated to the solvent regeneration. In this respect, sterically hindered amines are considered potential solvents for CO₂ capture. They provide a low energy requirement during the regeneration process due to its molecular structure. However, its absorption kinetics are slow and they must be promoted by blending with faster solvents such as monoethanolamine (MEA) and piperazine (PZ). In this work, the kinetic behavior of two sterically hindered amines were studied under partial oxy-combustion conditions and compared with MEA. A lab-scale semi-batch reactor was used. The CO₂ composition of the synthetic flue gas varied from 15%v/v – conventional coal combustion – to 60%v/v – maximum CO₂ concentration allowable for an optimal partial oxy-combustion operation. Firstly, 2-amino-2-methyl-1-propanol (AMP) showed a hybrid behavior with fast kinetics and a low enthalpy of CO₂ absorption. The second solvent was Isophrondiamine (IF), which has a steric hindrance in one of the amino groups. Its free amino group increases its cyclic capacity. In general, the presence of higher CO₂ concentration in the flue gas accelerated the CO₂ absorption phenomena, producing higher CO₂ absorption rates. In addition, the evolution of the CO2 loading also exhibited higher values in the experiments using higher CO₂ concentrated flue gas. The steric hindrance causes a hybrid behavior in this solvent, between both fast and slow kinetic solvents. The kinetics rates observed in all the experiments carried out using AMP were higher than MEA, but lower than the IF. The kinetic enhancement experienced by AMP at a high CO2 concentration is slightly over 60%, instead of 70% – 80% for IF. AMP also improved its CO₂ absorption capacity by 24.7%, from 15%v/v to 60%v/v, almost double the improvements achieved by MEA. In IF experiments, the CO₂ loading increased around 10% from 15%v/v to 60%v/v CO₂ and it changed from 1.10 to 1.34 mole CO₂ per mole solvent, more than 20% of increase. This hybrid kinetic behavior makes AMP and IF promising solvents for partial oxy–combustion applications.

Keywords: absorption, carbon capture, partial oxy-combustion, solvent

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Authors: M. Najafi, S. Bab, F. Rahimi Dehgolan

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The motion of an axially moving beam with rotating prismatic joint with a tip mass on the end is analyzed to investigate the nonlinear vibration and dynamic stability of the beam. The beam is moving with a harmonic axially and rotating velocity about a constant mean velocity. A time-dependent partial differential equation and boundary conditions with the aid of the Hamilton principle are derived to describe the beam lateral deflection. After the partial differential equation is discretized by the Galerkin method, the method of multiple scales is applied to obtain analytical solutions. Frequency response curves are plotted for the super harmonic resonances of the first and the second modes. The effects of non-linear term and mean velocity are investigated on the steady state response of the axially moving beam. The results are validated with numerical simulations.

Keywords: super harmonic resonances, non-linear vibration, axially moving beam, Galerkin method

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Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

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Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: sound detection, impulsive signal, background noise, neural network

Procedia PDF Downloads 319

Authors: Yaser Miaji, Mohammad Sabbagh

Abstract:

Radio Frequency Identification (RFID) is a technology which shares a similar concept with bar code. With RFID, the electromagnetic or electrostatic coupling in the RF portion of the electromagnetic spectrum is used to transmit signals. Supply chain management is aimed to keep going long-term performance of individual companies and the overall supply chain by maximizing customer satisfaction with minimum costs. One of the major issues in the supply chain management is product loss or shrinkage. In order to overcome this problem, this system which uses Radio Frequency Identification (RFID) technology will be able to RFID track and identify where losses are occurring and enable effective traceability. RFID brings a new dimension to supply chain management by providing a more efficient way of being able to identify and track items at the various stages throughout the supply chain. This system has been developed and tested to prove that RFID technology can be used to improve traceability in supply chain at low cost. Due to its simplicity in interface program and database management system using Visual Basic and MS Excel or MS Access the system can be more affordable and implemented even by small and medium scale industries.

Keywords: supply chain, RFID, tractability, radio frequency identification

Procedia PDF Downloads 488

Authors: Eudjen Cinc

Abstract:

The contemporary society, which is, whether we like it or not, oriented towards utilitarianism, pragmatics and professional flexibility, lives in a certain paradox. On the one hand, at least declaratively, the accent of modern society is on knowledge; knowledge is even considered to be a commodity, the popularity of education is increased as the only means of survival in the market-oriented world, while on the other hand modern society is moving towards simplification and decreasing the amount of information and areas which are considered necessary in the generally excepted concept of education. We cannot talk about the preschool teacher profession without mentioning work with gifted children. The preschool teacher knowing the characteristics of gifted children is of utmost importance because their early identification and professional guidance are of cardinal importance for the direction in which the children will develop. When we talk about musical ability, in the first phase, the role of preschool teachers in the identification and stimulation of gifted children naturally refers to monitoring children’s musical manifestation. The identification process and work with the gifted presupposes a good relationship with the family, synergy of these two important influences in the child’s education and upbringing.

Keywords: music education, gifted children, methodology, kindergarten

Procedia PDF Downloads 273

Authors: M. Heidari, A. Safekordi, A. Zamaniyan, E. Ganji Babakhani, M. Amanipour

Abstract:

Perovskite-type membrane Ba_0.5Sr_0.5Ce_0.9Y_0.1O_3-δ (BSCY) was successfully synthesized by liquid citrate method. The hydrogen permeation and stability of BSCY perovskite-type membranes were studied at high temperatures. The phase structure of the powder was characterized by X-ray diffraction (XRD). Scanning electron microscopy (SEM) was used to characterize microstructures of the membrane sintered under various conditions. SEM results showed that increasing in sintering temperature, formed dense membrane with clear grains. XRD results for BSCY membrane that sintered in 1150 °C indicated single phase perovskite structure with orthorhombic configuration, and SEM results showed dense structure with clear grain size which is suitable for permeation tests. Partial substitution of Sr with Ba in SCY structure improved the hydrogen permeation flux through the membrane due to the larger ionic radius of Ba²⁺. BSCY membrane shows high hydrogen permeation flux of 1.6 ml/min.cm² at 900 °C and partial pressure of 0.6.

Keywords: hydrogen separation, perovskite, proton conducting membrane.

Procedia PDF Downloads 341

Authors: Ravande Kishore

Abstract:

The paper present the results of experimental investigation carried out to understand the mechanical properties of concrete containing marble dust. Two grades of concrete viz. M25 and M35 have been considered for investigation. For each grade of concrete five replacement percentages of sand viz. 5%, 10%, 15%, 20% and 25% by marble dust have been considered. In all, 12 concrete mix cases including two control concrete mixtures have been studied to understand the key properties such as Compressive strength, Modulus of elasticity, Modulus of rupture and Split tensile strength. Development of Compressive strength is also investigated. In general, the results of investigation indicated improved performance of concrete mixture containing marble dust. About 21% increase in Compressive strength is noticed for concrete mixtures containing 20% marble dust and 80% river sand. An overall assessment of investigation results pointed towards high potential for marble dust as alternative construction material coming from waste generated in marble industry.

Keywords: construction material, partial replacement, marble dust, compressive strength

Procedia PDF Downloads 428

Authors: Ke Lin, Steve Wu Qing Yang, Zhang Nan

Abstract:

The medicine and drugs has in the past been manufactured to the final products and then used laboratory analysis to verify their quality. However the industry needs crucially a monitoring technique for the final batch to batch quality check. The introduction of process analytical technology (PAT) provides an incentive to obtain real-time information about drugs on the production line, with the following optical techniques being considered: near-infrared (NIR) spectroscopy, Raman spectroscopy and imaging, mid-infrared spectroscopy with the use of chemometric techniques to quantify the final product. However, presents problems in that the spectra obtained will consist of many combination and overtone bands of the fundamental vibrations observed, making analysis difficult. In this work, we describe a non-destructive system and method for capsule and liquid medicine identification, more particularly, using terahertz time-domain spectroscopy and/or designed terahertz portable system for identifying different types of medicine in the package of capsule or in liquid medicine bottles. The target medicine can be detected directly, non-destructively and non-invasively.

Keywords: terahertz, non-destructive, non-invasive, chemical identification

Procedia PDF Downloads 131

Authors: Dehini Rachid, Ferdi Brahim

Abstract:

The shunt active power filter (SAPF) is not destined only to improve the power factor, but also to compensate the unwanted harmonic currents produced by nonlinear loads. This paper presents a SAPF with identification and control method based on artificial neural network (ANN). To identify harmonics, many techniques are used, among them the conventional p-q theory and the relatively recent one the artificial neural network method. It is difficult to get satisfied identification and control characteristics by using a normal (ANN) due to the nonlinearity of the system (SAPF + fast nonlinear load variations). This work is an attempt to undertake a systematic study of the problem to equip the (SAPF) with the harmonics identification and DC link voltage control method based on (ANN). The latter has been applied to the (SAPF) with fast nonlinear load variations. The results of computer simulations and experiments are given, which can confirm the feasibility of the proposed active power filter.

Keywords: artificial neural networks (ANN), p-q theory, harmonics, total harmonic distortion

Procedia PDF Downloads 386

Authors: V. Lokesh, M. Manjunathan, S. Sairam, K. Saithsh Kumar, R. Anantharaj

Abstract:

The densities of pure and its binary mixtures of 1-Butyl-3-methyl imidazolium bis (trifluoro methyl sulfonyl) imide and 1–Ethyl-3-methyl imidazolium ethyl sulphate at different temperature, over the entire composition range were measured at 293.15, 298.15, 303.15, 308.15, 313.15, 318.15, 323.15, 328.15, 33.15, 338.15, 343.15 K. In this study, the liquid-liquid extraction procedure was used. From this experimental data, the excess molar volumes, apparent molar volume, partial molar volumes and the excess partial molar volumes have been calculated for over the whole composition range. Hence, the effect of temperature and composition on all derived thermodynamic properties of this binary mixture will be discussed in terms of intermolecular interactions.

Keywords: ionic liquid, interaction energy, effect of temperature, effect of composition

Procedia PDF Downloads 172

Authors: Graziella Ziino, Filippo Giarratana, Stefania Maria Marotta, Alessandro Giuffrida, Antonio Panebianco

Abstract:

In Europe, North America and Japan, campylobacteriosis is one of the leading food-borne bacterial illnesses, often related to the consumption of poultry meats and/or by-products. The aim of this study was the evaluation of Campylobacter contamination of poultry meats marketed in Sicily (Italy) using both traditional methods and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS). MALDI-TOF MS is considered a promising rapid (less than 1 hour) identification method for food borne pathogens bacteria. One hundred chicken and turkey meat preparations (no. 68 hamburgers, no. 21 raw sausages, no. 4 meatballs and no. 7 meat rolls) were taken from different butcher’s shops and large scale retailers and submitted to detection/enumeration of Campylobacter spp. according to EN ISO 10272-1:2006 and EN ISO 10272-2:2006. Campylobacter spp. was detected with general low counts in 44 samples (44%), of which 30 from large scale retailers and 14 from butcher’s shops. Chicken meats were significantly more contaminated than turkey meats. Among the preparations, Campylobacter spp. was found in 85.71% of meat rolls, 50% of meatballs, 44.12% of hamburgers and 28.57% of raw sausages. A total of 100 strains, 2-3 from each positive samples, were isolated for the identification by phenotypic, biomolecular and MALDI-TOF MS methods. C. jejuni was the predominant strains (63%), followed by C. coli (33%) and C. lari (4%). MALDI-TOF MS correctly identified 98% of the strains at the species level, only 1% of the tested strains were not identified. In the last 1%, a mixture of two different species was mixed in the same sample and MALDI-TOF MS correctly identified at least one of the strains. Considering the importance of rapid identification of pathogens in the food matrix, this method is highly recommended for the identification of suspected colonies of Campylobacteria.

Keywords: campylobacter spp., Food Microbiology, matrix-assisted laser desorption ionization-time of flight mass spectrometry, rapid microbial identification

Procedia PDF Downloads 292